Abstract

Academics and industry professionals have shown considerable interest in the study of product maps in e-commerce because of the insights they give regarding the relationship between items, including their complementarity and rivalry. Existing research, however, has mostly relied on the input of big manufacturers and merchants and data collected from these authoritative sources. In this article, we use a crowdsourced bottom-up methodology, utilising SME e-commerce sites as the primary sources of information. This method permits distributed data processing and the synthesis of viewpoints and information from several distinct sources. In order to quantify product similarities and construct a product map, a graph term frequency-inverse document frequency approach is provided. Using information on more than 90,000 goods from 52 SME sites, a hierarchical community structure was discovered using this technique. The findings revealed a localised distribution pattern for goods produced on the same location. Our research may help online marketplaces increase their product variety via more calculated pricing and inventory management.

Description